library(palmerpenguins)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
head(penguins,5)
## # A tibble: 5 × 8
## species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
## <fct> <fct> <dbl> <dbl> <int> <int>
## 1 Adelie Torgersen 39.1 18.7 181 3750
## 2 Adelie Torgersen 39.5 17.4 186 3800
## 3 Adelie Torgersen 40.3 18 195 3250
## 4 Adelie Torgersen NA NA NA NA
## 5 Adelie Torgersen 36.7 19.3 193 3450
## # ℹ 2 more variables: sex <fct>, year <int>
tail(penguins,5)
## # A tibble: 5 × 8
## species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
## <fct> <fct> <dbl> <dbl> <int> <int>
## 1 Chinstrap Dream 55.8 19.8 207 4000
## 2 Chinstrap Dream 43.5 18.1 202 3400
## 3 Chinstrap Dream 49.6 18.2 193 3775
## 4 Chinstrap Dream 50.8 19 210 4100
## 5 Chinstrap Dream 50.2 18.7 198 3775
## # ℹ 2 more variables: sex <fct>, year <int>
levels(penguins$species)
## [1] "Adelie" "Chinstrap" "Gentoo"
levels(penguins$sex)
## [1] "female" "male"
count(penguins,sex)
## # A tibble: 3 × 2
## sex n
## <fct> <int>
## 1 female 165
## 2 male 168
## 3 <NA> 11
ggplot(penguins,aes(flipper_length_mm,body_mass_g,colour = sex)) +
geom_point() +
geom_smooth(method='lm')+
theme_minimal()+
ggthemes::theme_tufte() +
ggtitle("Relationship between flipper_length and body mass based on sex")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_smooth()`).
## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_point()`).
The plot shows relationship between flipper_length and body mass
differentiated by sex. ggthemes:: theme_tufte() removes the unnecessary
background grids and colours.
library(plotly)
## Warning: package 'plotly' was built under R version 4.4.2
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
Plotly is an interactive graphing library for R that makes it easy to create interactive, web-ready visualizations. It is particularly useful for exploring data, sharing findings, and building dashboards with enhanced user experiences.
relationship <- ggplot(penguins,aes(flipper_length_mm,body_mass_g,colour = sex)) +
geom_point() +
geom_smooth(method='lm')+
theme_minimal()+
ggthemes::theme_tufte() +
ggtitle("Relationship between flipper_length and body mass based on sex")
ggplotly(relationship)
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_smooth()`).
ggplot(data = penguins, aes(x = flipper_length_mm)) +
geom_histogram(aes(fill = species), alpha = 0.5, position = "identity") +
scale_fill_manual(values = c("darkorange","darkorchid","cyan4"))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_bin()`).
Flipper <- ggplot(data = penguins, aes(x = flipper_length_mm)) +
geom_histogram(aes(fill = species), alpha = 0.5, position = "identity") +
scale_fill_manual(values = c("darkorange","darkorchid","cyan4"))
ggplotly(Flipper)
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_bin()`).